Redefault Risk After the Mortgage Crisis

 

A tower filled with shredded U.S. currency in the lobby of the Federal Reserve Bank of Philadelphia.

Paul Calem et al. of the Phillie Fed posted Redefault Risk in the Aftermath of the Mortgage Crisis: Why Did Modifications Improve More Than Self-Cures? The abstract reads,

This paper examines the redefault rate of mortgages that were selected for modification during 2008–2011, compared with that of similarly situated self-cured mortgages during the same period. We find that while the performance of both modified and self-cured loans improved dramatically over this period, the decline in the redefault rate for modified loans was substantially larger, and we attribute this difference to a few key factors. First, the repayment terms provided by modifications became increasingly generous, including the more frequent offering of principal reduction, resulting in greater financial relief to borrowers. Second, the later modifications also benefited from improving economic conditions — modification became more effective as unemployment rates declined and home prices recovered. Third, we find that the difference in redefault rate improvement between modified loans and self-cured loans is not fully explained by observable risk and economic variables. We attribute this residual difference to the servicers’ learning process — so-called learning by doing. Early in the mortgage crisis, many servicers had limited experience selecting the best borrowers for modification. As modification activity increased, lenders became more adept at screening borrowers for modification eligibility and in selecting appropriate modification terms.

The big question, of course, is what does this all tell us about preparing for the next crisis? That crisis, no doubt, won’t be a repeat of the last one. But it will likely rhyme with it enough — falling home prices, increasing defaults — that we can draw some lessons. One is that we did not use principal reductions fast enough to make a big difference in how the crisis played out. There were a lot of reason for this, some legit and some not. But if it is good public policy overall, we should set up mechanisms to deploy principal reduction early in the next crisis so that we do not need to navigate all of the arguments about moral hazard while knee deep in it.

Economic Factors That Affect Housing Prices

photo by TaxRebate.org.uk

S&P has posted a paper on Economic Factors That Affect Housing Prices. This is, of course, an important topic, albeit one that is an art as well as a science. While S&P undertook this analysis more for mortgage-backed securities investors than for anyone else, it certainly is of use to the rest of us. The paper opens,

The U.S. domestic housing market has experienced a 23% price increase since the beginning of the housing recovery in 2011. Many local housing markets are now close to or above their peak levels of 2006, which leads us to investigate whether the pace of home price appreciation (HPA) can continue at its current pace. In this paper, we (1) examine the economic factors that influence HPA and (2) forecast HPA for numerous geographic regions assuming various economic conditions over the next five years. While the aggregate national pattern in housing prices is an important reference, we need to examine housing prices at a more granular geographic level in order to understand regional housing market dynamics and learn how these are affected by local macroeconomic factors. This paper demonstrates that several economic variables are needed to predict average home price movements for each of 48 different U.S. metropolitan statistical areas (MSAs).

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Factors that influence HPA can be difficult to predict. Therefore, residential mortgage backed securities (RMBS) investors frequently use a range of HPA projections to estimate their potential bond returns. With that in mind, for each MSA, we considered five separate hypothetical economic scenarios, ranging from an “Upside” forecast to an extreme “Stress 3” case. Interestingly, our Stress 3 case forecasts a 28% decline in HPI at the national level over the next five years, which corresponds roughly to the decline experienced in the last recession. Our “base case” scenario leads to forecasts at the national level of a 26% increase in HPI over five years. This represents what we believe to be the most likely economic forecast. (1-2)

S&P’s key findings include:

  • Movement in HPA is primarily influenced by up to five variables, depending on the MSA: housing affordability, changes in shadow inventory, the unemployment rate, the TED spread [a measure of distress in the credit markets], and population growth.
  • HPA in many MSAs has momentum, meaning that it depends on its level in the previous quarter of observation.
  • The mortgage rate generally appears to have little predictive power in connection with home prices.
  • Chicago, Houston, Boston, and San Francisco are projected to appreciate at a greater pace (45%, 40%, 27%, and 36%, respectively) than the 26% forecast for the nation as a whole over the next five years, and New York at a slower pace (21%). Columbus led all MSAs with a projected five-year HPA of 50%.
  • Under our most pessimistic (Stress 3) scenario, Chicago is forecast to experience a greater decline in HPI (34%) over the next five years than the nation as a whole (29%), while New York, Boston, Houston, and San Francisco are projected to experience declines that are less severe than that of the nation (19%, 3%, 17%, and 16%, respectively). Markets that have been vulnerable in the past (Las Vegas, Phoenix, and Riverside) are projected to experience the greatest five-year declines under our Stress 3 scenario (66%, 68%, and 68%). The markets that show the greatest movements are the most sensitive to the five factors and frequently show the greatest upside and downside. (2-3, emphasis in the original)

I found the first and third bullet points to be the most interesting, as many pundits weigh in on the factors that affect housing prices. It will be interesting to see if further research confirms S&P’s findings.